fix sentences and improve readability

m-reuter · m-reuter · commit 4c63d96155cf · 2026-02-13T18:00:28.000+01:00
diff --git a/LICENSE b/LICENSE
@@ -1,7 +1,7 @@
 The MIT License (MIT)
 
 Copyright (c) 2014 fraser-lab
-Copyright (c) 2020 DeepMI-lab
+Copyright (c) 2020-2026 DeepMI-lab
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal
diff --git a/README.md b/README.md
@@ -1,5 +1,14 @@
-# Deep-MI.github.io
+# Deep-MI Lab Website
 
+This is the official website for the Deep Medical Imaging (Deep-MI) Lab.
+
+The website is built with Jekyll and hosted on GitHub Pages.
+
+## Quick Links
+
+- **Live Website**: [https://deep-mi.github.io](https://deep-mi.github.io)
+- **Contributing**: See [CONTRIBUTING.md](CONTRIBUTING.md)
+- **Quick Start**: See [QUICKSTART.md](QUICKSTART.md)
 
 ## Create News Posts
 
@@ -82,16 +91,17 @@ cp scripts/pre-commit.sh .git/hooks/pre-commit
 chmod +x .git/hooks/pre-commit
 ```
 
-## Sources
+For more detailed guidelines, see [CONTRIBUTING.md](CONTRIBUTING.md).
 
-This website was built using the Fraser Lab [website](http://fraserlab.com/) as a template.  James Fraser's website is open-source and available on [Github](https://github.com/fraser-lab/fraser-lab.github.io)
+## Attribution
 
+This website was built using the [Fraser Lab website](http://fraserlab.com/) as a template. James Fraser's website is open-source and available on [GitHub](https://github.com/fraser-lab/fraser-lab.github.io).
 
-Technologies this website uses:
+### Technologies Used
 
-    Jekyll
-    Github Pages
-    Twitter Bootstrap 4.4.1
+- Jekyll - Static site generator
+- GitHub Pages - Hosting
+- Bootstrap 4.4.1 - CSS framework
 
 ## Local Development
 
diff --git a/_posts/2020-03-07-New-Webpage.md b/_posts/2020-03-07-New-Webpage.md
@@ -6,19 +6,19 @@ group: news
 ---
 Today we finally took the time out of the always-busy schedule of writing grants and papers and created an initial version of the
 DeepMI Lab Webpage. This step has long been overdue and we are happy to present it to the world.
-There has been a long discussion how to solve mutliple problems at the same time:
+There has been a long discussion how to solve multiple problems at the same time:
 
 - how can we have a webpage that is flexible, yet easy to maintain for more than one curator
 - how can we represent the fact that the Lab is associated across multiple institutions
 - how can we version control the page, edit quickly without local IT
-- where can we host it 
+- where can we host it
 - and how should we even call the lab (I vetoed Reuter-Lab)
 
 The first few points were solved by starting with github.io and jekyll - easy. The name was another beast!
 The Lab's background is in developing computational methods for medical image analysis. We did this since 2008 and recently people
 like to call it AI (basically whenever a computer does something cool, like analyze an image). Most of our recent methods are
 deep-learning based, extending existing architectures for specific goals, e.g. brain MRI segmentation.
 This is why Deep Medical Imaging Lab (DeepMI) was selected. Yet, we are not limited to deep-learning and have a lot of work on traditional
-methods (robust image registration, shape analysis, geometry processing etc). So expect to see some variety. 
+methods (robust image registration, shape analysis, geometry processing etc). So expect to see some variety.
 
 We hope you enjoy this site. Please contact us with any comments. We look forward hearing from you ...
diff --git a/index.md b/index.md
@@ -1,19 +1,19 @@
 ---
-title: Deep MI Lab 
+title: Deep MI Lab
 layout: home
 group: home
 ---
 
 # Welcome to Deep MI Lab!
 {: .display-4}
 
-Our research is focused on the development of novel computational methods (deep-learning, AI) for the automated analysis, segmentation, classification, diagnosis and prognosis of medical imaging data to support the study of neurodegenerative diseases.
+Our research focuses on the development of novel computational methods (deep learning, AI) for the automated analysis, segmentation, classification, diagnosis, and prognosis of medical imaging data to support the study of neurodegenerative diseases.
 {: .welcomefont}
 
 We are part of the:
 {: .welcomefont}
 
-- [German Center for Neurodegenerative Diseases, Bonn, Germany](https://www.dzne.de/en/research/research-areas/population-health-sciences/forschungsgruppen/reuter/research-areasfocus/) 
+- [German Center for Neurodegenerative Diseases, Bonn, Germany](https://www.dzne.de/en/research/research-areas/population-health-sciences/forschungsgruppen/reuter/research-areasfocus/)
 - [Martinos Center for Biomedical Imaging, MGH/HMS Boston, USA](https://www.martinos.org/investigator/martin-reuter/)
 - and associated to [MIT CSAIL](http://reuter.mit.edu).
 {: .welcomefont}
diff --git a/join/index.md b/join/index.md
@@ -20,33 +20,33 @@ While every lab member is expected to contribute to the lab, we also expect to g
 - We strive to provide excellent training across a wide range of computational and experimental techniques.
 - We provide a strong network of international collaborators at various prestigious institutions, such as Harvard and MIT.
 - We are located at DZNE, a German Helmholtz Center, with outstanding funding, resources, and research environment.
-- We have access to exciting and richly phenotyped datasets, e.g. the Rhineland Study (a large population study with thousdands of participants).
+- We have access to exciting and richly phenotyped datasets, e.g. the Rhineland Study (a large population study with thousands of participants).
 - We currently train on 24 NVIDIA V100 (32 GB each, NVlink'ed) and 8 A100 GPUs (40 GB each) available exclusively for our lab.
 - We provide access to the DZNE HPC cluster with 94 V100 GPU's.
 - We have a modern MRI facility in house (with a 3T and a 7T Siemens scanner), and further 3T scanners at two scan centers.
-- We have strong local collaborative ties with clinial science, population science, neuroscience, radiology, epileptiology etc.
+- We have strong local collaborative ties with clinical science, population science, neuroscience, radiology, epileptiology etc.
 - We develop FastSurfer and contribute to FreeSurfer (a popular open source software suite for brain MRI processing) via collaborations at Harvard Medical School.
-- ... (if you are not yet convicend, please ask)
+- ... (if you are not yet convinced, please ask)
 
 # Postdoctoral Fellows
 
 We currently do not have any open positions, sorry.
 
 <!-- Inquiries about Postdoctoral positions should be emailed directly to Martin Reuter (use Subject: MIC-PD-JOIN). Our lab welcomes applicants of any race, religion, national origin, gender identity, caregiver and family commitments, political affiliation, and eligible age or ability. Furthermore, we are committed to maintaining a supportive and collaborative lab environment. Our lab doesn’t always post for specific positions, so please reach out! We are interested in hearing about your scientific background and goals. -->
 
-As a member of the Humboldt Foundation Network, we would love to host you via a prestigious postdoctoral [Humboldt Fellowship](https://www.humboldt-foundation.de/bewerben/foerderprogramme/humboldt-forschungsstipendium) for a stay of 6 - 24 months at the Deep-MI Lab in Germany! Please contact us. 
+As a member of the Humboldt Foundation Network, we would love to host you via a prestigious postdoctoral [Humboldt Fellowship](https://www.humboldt-foundation.de/bewerben/foerderprogramme/humboldt-forschungsstipendium) for a stay of 6 - 24 months at the Deep-MI Lab in Germany! Please contact us.
 
 # Graduate Students
 
-Sadly, we currently do not have any open PhD positions. If you obtained a PhD fellowship or are exploring external funding possibilities and would like to visit or stay at our Lab, please contact us. 
+Sadly, we currently do not have any open PhD positions. If you obtained a PhD fellowship or are exploring external funding possibilities and would like to visit or stay at our Lab, please contact us.
 
 # Master Students
 
 We can offer various exciting topics for your Master Thesis project in our lab. Please contact us for details.
 
 # Other
 
-In the past, our lab has enjoyed having foreign exchange students, interns, (sabbatical) visitors from academia and industry. 
+In the past, our lab has enjoyed having foreign exchange students, interns, (sabbatical) visitors from academia and industry.
 
 <p style="text-align: center;">
 ![alt text](/static/img/join/bonn.jpg "Bonn")
diff --git a/research/fastsurfer.md b/research/fastsurfer.md
@@ -89,7 +89,7 @@ To ensure the usefulness of our entire pipeline, FastSurfer was extensively vali
 
 #### 1. Accuracy and Generalizability - How good is the whole brain segmentation generated by FastSurferCNN?
 
-__Answer__: Very good! FastSurcerCNN outperforms other deep-learning architectures by a significant margin both wrt to FreeSurfer
+__Answer__: Very good! FastSurferCNN outperforms other deep-learning architectures by a significant margin both wrt to FreeSurfer
 and a manual standard (Mindboggle). It generalizes well across five different datasets including subjects with different disease states (e.g.
 cognitive normal, mild cognitive impaired or demented subjects in OASIS, ADNI, MIRIAD), different
 vendors (e.g. THP), age groups, downsampled and defaced images (e.g. HCP) and alternative T1-imaging protocols (e.g. MIRIAD)
diff --git a/research/index.md b/research/index.md
@@ -15,10 +15,10 @@ The lab is committed to publishing our code ( [Deep-MI Github](https://github.co
 # Research Directions
 
 
-  The research focus the DeepMI lab is on the development of a novel deep-learning (CNNs) and machine-learning 
-  methods for the automated analysis of medical images, such as human brain MRI. 
-  In addition to medical image computing and computational neuroimaging, our research intersets include
-   computational geometry and topology, computer and 
+  The research focus of the DeepMI lab is on the development of novel deep-learning (CNNs) and machine-learning
+  methods for the automated analysis of medical images, such as human brain MRI.
+  In addition to medical image computing and computational neuroimaging, our research interests include
+   computational geometry and topology, computer and
    biomedical vision, computer-aided design, geometric modeling and computer graphics.
 
 <!---
@@ -43,14 +43,14 @@ In close collaboration with clinical and industrial partners, we develop the nex
 
 # Selected Projects
 
- - [FastSurfer](/research/fastsurfer/), a deep-learning based neuroimaging Pipeline 
+ - [FastSurfer](/research/fastsurfer/), a deep-learning based neuroimaging Pipeline
  - [FatSegNet](/research/fatsegnet/), automated adipose tissue segmentation and field-of-view estimation in Dixon MRI
  - [BrainPrint](/research/brainprint/), tools for shape and asymmetry analysis of neuroanatomical structures
  - [p3CNN](/research/spherical/), cortical surface segmentation
  - [LaPy](/LaPy/), Python Library for geometric mesh processing and FEM differential geometry computations
  - [fsqc](/fsqc/), Quality check tools for FastSurfer and FreeSurfer output
  - [WhipperSnapPy](/WhipperSnapPy/), Python OpenGL tool to take screenshots of surfaces and overlays
- 
+
 
 <!---
 <img class="img-fluid mx-auto d-block" src="/static/img/image.jpg" alt="whatever">
